docstr: Parameters
  ----------
  term_doc_matrix : TermDocMatrix
          TermDocMatrix (or descendant) which will be used in constructing square.
  category_a_list : list
          Category names for term A
  category_b_list : list
          Category names for term B (in opposition to A)
  not_category_a_list : list
          List of category names that belong to not A
  not_category_b_list : list
          List of category names that belong to not A
  labels : dict
          None by default. Labels are dictionary of {'a_and_b': 'A and B', ...} to be shown
          above each category.
  term_ranker : TermRanker
          Class for returning a term-frequency convention_df
  scorer : termscoring class, optional
          Term scoring class for lexicon mining. Default: `scattertext.termscoring.ScaledFScore`
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code: def __init__(
      self,
      term_doc_matrix,
      category_a_list,
      category_b_list,
      not_category_a_list,
      not_category_b_list,
      labels=None,
      term_ranker=AbsoluteFrequencyRanker,
      scorer=None,
  ):
      """
      Parameters
      ----------
      term_doc_matrix : TermDocMatrix
              TermDocMatrix (or descendant) which will be used in constructing square.
      category_a_list : list
              Category names for term A
      category_b_list : list
              Category names for term B (in opposition to A)
      not_category_a_list : list
              List of category names that belong to not A
      not_category_b_list : list
              List of category names that belong to not A
      labels : dict
              None by default. Labels are dictionary of {'a_and_b': 'A and B', ...} to be shown
              above each category.
      term_ranker : TermRanker
              Class for returning a term-frequency convention_df
      scorer : termscoring class, optional
              Term scoring class for lexicon mining. Default: `scattertext.termscoring.ScaledFScore`
      """
  
      self.category_a_list_ = category_a_list
      self.category_b_list_ = category_b_list
      self.not_category_a_list_ = not_category_a_list
      self.not_category_b_list_ = not_category_b_list
      assert set(self._get_all_categories()) & set(
          term_doc_matrix.get_categories()
      ) == set(self._get_all_categories())
      self._build_square(term_doc_matrix, term_ranker, labels, scorer)
  
file_path: scattertext/scattertext/semioticsquare/FourSquare.py
imports: from scattertext.semioticsquare import SemioticSquare
  from scattertext.termranking import AbsoluteFrequencyRanker
label_desc: Use image node_id 1 to create a new FourSquare object from inherited base classes: SemioticSquare with example: obj = FourSquare(term_doc_matrix, category_a_list, category_b_list, not_category_a_list, not_category_b_list, labels, term_ranker, scorer)